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arXiv · 2304.01843

Reconfigurable Intelligent Surfaces: Interplay of Unit-Cell- and Surface-Level Design and Performance under Quantifiable Benchmarks

Ammar Rafique·Naveed Ul Hassan·Muhammad Zubair·Ijaz Haider Naqvi·Muhammad Qasim Mehmood·Chau Yuen·Marco Di Renzo·Merouane Debbah
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Abstract

The ability of reconfigurable intelligent surfaces (RIS) to produce complex radiation patterns in the far-field is determined by various factors, such as the unit-cell's size, shape, spatial arrangement, tuning mechanism, the communication and control circuitry's complexity, and the illuminating source's type (point/planewave). Research on RIS has been mainly focused on two areas: first, the optimization and design of unit-cells to achieve desired electromagnetic responses within a specific frequency band; and second, exploring the applications of RIS in various settings, including system-level performance analysis. The former does not assume any specific radiation pattern on the surface level, while the latter does not consider any particular unit-cell design. Both approaches largely ignore the complexity and power requirements of the RIS control circuitry. As we progress towards the fabrication and use of RIS in real-world settings, it is becoming increasingly necessary to consider the interplay between the unit-cell design, the required surface-level radiation patterns, the control circuit's complexity, and the power requirements concurrently. In this paper, a benchmarking framework for RIS is employed to compare performance and analyze tradeoffs between the unit-cell's specified radiation patterns and the control circuit's complexity for far-field beamforming, considering different diode-based unit-cell designs for a given surface size. This work lays the foundation for optimizing the design of the unit-cells and surface-level radiation patterns, facilitating the optimization of RIS-assisted wireless communication systems.

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Ammar Rafique, Naveed Ul Hassan, Muhammad Zubair, Ijaz Haider Naqvi, Muhammad Qasim Mehmood, Chau Yuen, Marco Di Renzo, Merouane Debbah. 2023-04-04. Reconfigurable Intelligent Surfaces: Interplay of Unit-Cell- and Surface-Level Design and Performance under Quantifiable Benchmarks. https://arxiv.org/abs/2304.01843

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